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Enabling Neuroprostheses via Machine Learning
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AI
DOI：10.1007/s11633-025-1571-3.png)
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Abstract
En 中文
Neuroprostheses aim to repair and replace damaged sensory brain functions such as vision, hearing and touch, improve cognitive functions such as memory, and control arms through electrical stimulations in motor cortex or peripheral nerves. Through review of the progress and status of different neuroprostheses, we found an increasing role of machine learning in achieving complex prosthetic functions with groundbreaking results. This article provides a perspective on the role of machine learning in neuroprostheses designs and envisions future involvement of machine learning for more capable neuroprostheses in revolutionizing the treatment of neurological disorders and disabilities.
Keywords:
Neuroprostheses
machine learning
brain machine interface
neural signal decoding
brain stimulations
Journal
IF:
8.7
Papers:
301
Citations:
882